Those ones were the expensive headcount anyway

Arstechnica reports on a study where they measured the productivity of software developers of different open source projects doing different (also non-coding) tasks.

In the comments there’s a snarky summary of the articles main point:

“These factors lead the researchers to conclude that current AI coding tools may be particularly ill-suited to “settings with very high quality standards, or with many implicit requirements (e.g., relating to documentation, testing coverage, or linting/formatting) that take humans substantial time to learn.” While those factors may not apply in “many realistic, economically relevant settings” involving simpler code bases, they could limit the impact of AI tools in this study and similar real-world situations.”

So as long as I cull the experienced people and commit to lousy software the glorious Age of AI will deliver productivity gains? Awesome, those ones were the expensive headcount!

We’ll Ask The AI How to Make Money

We have no current plans to make revenue.

We have no idea how we may one day generate revenue.

We have made a soft promise to investors that once we’ve built a general intelligence system, basically we will ask it to figure out a way to generate an investment return for you.

Sam Altman to VCs in 2024

A video of this memorable moment … you can’t make this up.

Best “AI”-Rant

Most organizations cannot ship the most basic applications imaginable with any consistency, and you’re out here saying that the best way to remain competitive is to roll out experimental technology that is an order of magnitude more sophisticated than anything else your I.T department runs, which you have no experience hiring for, when the organization has never used a GPU for anything other than junior engineers playing video games with their camera off during standup, and even if you do that all right there is a chance that the problem is simply unsolvable due to the characteristics of your data and business? This isn’t a recipe for disaster, it’s a cookbook for someone looking to prepare a twelve course fucking catastrophe.

How about you remain competitive by fixing your shit? I’ve met a lead data scientist with access to hundreds of thousands of sensitive customer records who is allowed to keep their password in a text file on their desktop, and you’re worried that customers are best served by using AI to improve security through some mechanism that you haven’t even come up with yet? You sound like an asshole and I’m going to kick you in the jaw until, to the relief of everyone, a doctor will have to wire it shut, giving us ten seconds of blessed silence where we can solve actual problems.

After some general ranting the author answers several common “reasons” why a company might want to use LLMs/AI tools.